[NeurIPS 2023] Global Structure-Aware Diffusion Process for Low-Light Image Enhancement
🖥 Github: https://github.com/jinnh/GSAD
📕 Paper: https://arxiv.org/pdf/2310.17577.pdf
🔥 Datasets: https://paperswithcode.com/dataset/lol
Forwarded from Python | Machine Learning | Coding | R
CS25: Transformers United V3
New lectures on the course on Transformers from Stanford! Stanford CS 25 " Transformers United " featured celebrity guests such as Andriy Karpaty, Noam Brown, Lukas Beyer and Geoff Hinton himself!
A new report has been released on the creation and recipes for creating universal AI agents in open worlds:
🟢 MineDojo : an open framework and multimodal database for training Minecraft agents.
🟢 Voyager : agent for lifelong learning in Minecraft based on LLM.
🟢 Eureka: GPT-4 develops reward functions to teach a robot hand to turn a knob.
🟢 VIMA : one of the earliest multimodal LLMs.
🟢A look into the future: promising areas of research.
☑️ Slides : https://drive.google.com/file/d/1lWIhijUaTZkkWOC_YwZHMoI0h7EAWVPL/view
📑 Lectures : https://web.stanford.edu/class/cs25
👌 https://t.iss.one/CodeProgrammer
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New lectures on the course on Transformers from Stanford! Stanford CS 25 " Transformers United " featured celebrity guests such as Andriy Karpaty, Noam Brown, Lukas Beyer and Geoff Hinton himself!
A new report has been released on the creation and recipes for creating universal AI agents in open worlds:
🟢 MineDojo : an open framework and multimodal database for training Minecraft agents.
🟢 Voyager : agent for lifelong learning in Minecraft based on LLM.
🟢 Eureka: GPT-4 develops reward functions to teach a robot hand to turn a knob.
🟢 VIMA : one of the earliest multimodal LLMs.
🟢A look into the future: promising areas of research.
☑️ Slides : https://drive.google.com/file/d/1lWIhijUaTZkkWOC_YwZHMoI0h7EAWVPL/view
📑 Lectures : https://web.stanford.edu/class/cs25
👌 https://t.iss.one/CodeProgrammer
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☑ PERF: Panoramic Neural Radiance Field from a Single Panorama
🖥 Github: https://github.com/perf-project/PeRF
⚡️Project: https://perf-project.github.io/
📕 Paper: https://arxiv.org/abs/2310.16831v1
⏩ Dataset: https://paperswithcode.com/dataset/replica
https://t.iss.one/DataScienceT
🖥 Github: https://github.com/perf-project/PeRF
⚡️Project: https://perf-project.github.io/
📕 Paper: https://arxiv.org/abs/2310.16831v1
⏩ Dataset: https://paperswithcode.com/dataset/replica
https://t.iss.one/DataScienceT
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Human-Guided Complexity-Controlled Abstractions
🖥 Github: https://github.com/mycal-tucker/human-guided-abstractions
📕 Paper: https://arxiv.org/pdf/2310.17550v1.pdf
🔥 Datasets: https://paperswithcode.com/dataset/fashion-mnist
https://t.iss.one/DataScienceT
🖥 Github: https://github.com/mycal-tucker/human-guided-abstractions
📕 Paper: https://arxiv.org/pdf/2310.17550v1.pdf
🔥 Datasets: https://paperswithcode.com/dataset/fashion-mnist
https://t.iss.one/DataScienceT
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DialogLLMScenic
🖥 Github: https://github.com/avmb/dialogllmscenic
📕 Paper: https://arxiv.org/pdf/2310.17372v1.pdf
🔥 Datasets: https://paperswithcode.com/dataset/carla
⭐ Tasks: https://paperswithcode.com/task/self-driving-cars
https://t.iss.one/DataScienceT
🖥 Github: https://github.com/avmb/dialogllmscenic
📕 Paper: https://arxiv.org/pdf/2310.17372v1.pdf
🔥 Datasets: https://paperswithcode.com/dataset/carla
⭐ Tasks: https://paperswithcode.com/task/self-driving-cars
https://t.iss.one/DataScienceT
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⚡️ LLMRec: Large Language Models with Graph Augmentation for Recommendation
🖥 Github: https://github.com/hkuds/llmrec
📕 Paper: https://arxiv.org/abs/2311.00423v1
⏩ Project: https://llmrec.github.io/
🌐 Dataset: https://llmrec.github.io/#
https://t.iss.one/DataScienceT
🖥 Github: https://github.com/hkuds/llmrec
📕 Paper: https://arxiv.org/abs/2311.00423v1
⏩ Project: https://llmrec.github.io/
🌐 Dataset: https://llmrec.github.io/#
https://t.iss.one/DataScienceT
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🖥 TORCH UNCERTAINTY
Comprehensive PyTorch Library for deep learning uncertainty quantification techniques.
🖥 Github: https://github.com/ensta-u2is/torch-uncertainty
📕 Paper: https://arxiv.org/abs/2311.01434v1
⏩ Project: https://llmrec.github.io/
👣 Api: https://torch-uncertainty.github.io/api.html
🌐 Dataset: https://paperswithcode.com/dataset/cifar-10
https://t.iss.one/DataScienceT
Comprehensive PyTorch Library for deep learning uncertainty quantification techniques.
pip install torch-uncertainty
🖥 Github: https://github.com/ensta-u2is/torch-uncertainty
📕 Paper: https://arxiv.org/abs/2311.01434v1
⏩ Project: https://llmrec.github.io/
👣 Api: https://torch-uncertainty.github.io/api.html
🌐 Dataset: https://paperswithcode.com/dataset/cifar-10
https://t.iss.one/DataScienceT
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PETA: Evaluating the Impact of Protein Transfer Learning with Sub-word Tokenization on Downstream Applications
🖥 Github: https://github.com/ginnm/proteinpretraining
📕 Paper: https://arxiv.org/pdf/2310.17415v1.pdf
🔥 Datasets: https://paperswithcode.com/dataset/peta-protein
⭐ Tasks: https://paperswithcode.com/task/language-modelling
🖥 Github: https://github.com/ginnm/proteinpretraining
📕 Paper: https://arxiv.org/pdf/2310.17415v1.pdf
🔥 Datasets: https://paperswithcode.com/dataset/peta-protein
⭐ Tasks: https://paperswithcode.com/task/language-modelling
https://t.iss.one/DataScienceT
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🎧 Video2Music: Suitable Music Generation from Videos using an Affective Multimodal Transformer model
Video2Music: Suitable Music Generation from Videos using an Affective Multimodal Transformer model.
🖥 Github: https://github.com/amaai-lab/video2music
📕 Paper: https://arxiv.org/abs/2311.00968v1
⏩ Demo: https://llmrec.github.io/
🌐 Dataset: https://zenodo.org/records/10057093
https://t.iss.one/DataScienceT
Video2Music: Suitable Music Generation from Videos using an Affective Multimodal Transformer model.
🖥 Github: https://github.com/amaai-lab/video2music
📕 Paper: https://arxiv.org/abs/2311.00968v1
⏩ Demo: https://llmrec.github.io/
🌐 Dataset: https://zenodo.org/records/10057093
https://t.iss.one/DataScienceT
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Data Science Math Skills (Free Course)
Enroll Link: https://www.clcoding.com/2023/10/data-science-math-skills-free-course.html?m=1
https://t.iss.one/DataScienceT
Enroll Link: https://www.clcoding.com/2023/10/data-science-math-skills-free-course.html?m=1
https://t.iss.one/DataScienceT
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Top execs from billion-dollar giants are whispering about next crypto "GEM". Want in?
This Tuesday, Blockchain Whispers pulls back the curtain. Join the insiders now: https://t.iss.one/+c5yEZuGFtsc5NDlk
This Tuesday, Blockchain Whispers pulls back the curtain. Join the insiders now: https://t.iss.one/+c5yEZuGFtsc5NDlk
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🔥 One of the most beautiful interactive visualizations on how LLMs work.
https://ig.ft.com/generative-ai/
https://t.iss.one/DataScienceT
https://ig.ft.com/generative-ai/
https://t.iss.one/DataScienceT
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🚀 Introducing YOLO-NAS Pose : A Game-Changer in Pose Estimation 🚀
This Model is a redefinition of pose estimation's potential.
🖥 Github: https://github.com/Deci-AI/super-gradients
📕 Notebook: https://colab.research.google.com/drive/1O4N5Vbzv0rfkT81LQidPktX8RtoS5A40
🚀 Demo: https://huggingface.co/spaces/Deci/YOLO-NAS-Pose-Demo
🌐 Colab: https://colab.research.google.com/drive/1agLj0aGx48C_rZPrTkeA18kuncack6lF
https://t.iss.one/DataScienceT
This Model is a redefinition of pose estimation's potential.
🖥 Github: https://github.com/Deci-AI/super-gradients
📕 Notebook: https://colab.research.google.com/drive/1O4N5Vbzv0rfkT81LQidPktX8RtoS5A40
🚀 Demo: https://huggingface.co/spaces/Deci/YOLO-NAS-Pose-Demo
🌐 Colab: https://colab.research.google.com/drive/1agLj0aGx48C_rZPrTkeA18kuncack6lF
https://t.iss.one/DataScienceT
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Bilingual Corpus Mining and Multistage Fine-Tuning for Improving Machine Translation of Lecture Transcripts
🖥 Github: https://github.com/shyyhs/CourseraParallelCorpusMining
📕 Paper: https://arxiv.org/abs/2311.03696v1
🔥 Datasets: https://paperswithcode.com/dataset/aspec
https://t.iss.one/DataScienceT
🖥 Github: https://github.com/shyyhs/CourseraParallelCorpusMining
📕 Paper: https://arxiv.org/abs/2311.03696v1
🔥 Datasets: https://paperswithcode.com/dataset/aspec
https://t.iss.one/DataScienceT
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Large Language Models (in 2023)
An excellent summary of the research progress and developments in LLMs.
Hyung Won chung, OpenAI (ex.Google and MIT Alumni) made this content publicly available. It's a great way to catch up on some important themes like scaling and optimizing LLMs.
Watch his talk here and Slides shared here.
https://t.iss.one/DataScienceT
An excellent summary of the research progress and developments in LLMs.
Hyung Won chung, OpenAI (ex.Google and MIT Alumni) made this content publicly available. It's a great way to catch up on some important themes like scaling and optimizing LLMs.
Watch his talk here and Slides shared here.
https://t.iss.one/DataScienceT
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🚀 Whisper-V3 / Consistency Decoder
Improved decoding for stable diffusion vaes.
- Whisper paper: https://arxiv.org/abs/2212.04356
- Whisper-V3 checkpoint: https://github.com/openai/whisper/discussions/1762
- Consistency Models: https://arxiv.org/abs/2303.01469
- Consistency Decoder release: https://github.com/openai/consistencydecoder
https://t.iss.one/DataScienceT
Improved decoding for stable diffusion vaes.
- Whisper paper: https://arxiv.org/abs/2212.04356
- Whisper-V3 checkpoint: https://github.com/openai/whisper/discussions/1762
- Consistency Models: https://arxiv.org/abs/2303.01469
- Consistency Decoder release: https://github.com/openai/consistencydecoder
https://t.iss.one/DataScienceT
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NVIDIA just made Pandas 150x faster with zero code changes.
All you have to do is:
Their RAPIDS library will automatically know if you're running on GPU or CPU and speed up your processing.
You can try it in this colab notebook
GitHub repo: https://github.com/rapidsai/cudf
https://t.iss.one/DataScienceT
All you have to do is:
%load_ext cudf.pandas
import pandas as pd
Their RAPIDS library will automatically know if you're running on GPU or CPU and speed up your processing.
You can try it in this colab notebook
GitHub repo: https://github.com/rapidsai/cudf
https://t.iss.one/DataScienceT
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